plop
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774ef275a4
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@ -65,7 +65,7 @@ def main():
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voice_path = tts_model.get_voice_path(args.voice)
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# CFG coef goes here because the model was trained with CFG distillation,
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# so it's not _actually_ doing CFG at inference time.
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# Also, if you are generating a dialog, you should have at least two voices in the list.
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# Also, if you are generating a dialog, you should have two voices in the list.
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condition_attributes = tts_model.make_condition_attributes(
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[voice_path], cfg_coef=2.0
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)
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@ -76,7 +76,6 @@ def main():
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pcms = queue.Queue()
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@torch.no_grad()
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def _on_frame(frame):
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if (frame != -1).all():
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pcm = tts_model.mimi.decode(frame[:, 1:, :]).cpu().numpy()
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@ -63,7 +63,7 @@
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"voice_path = tts_model.get_voice_path(voice)\n",
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"# CFG coef goes here because the model was trained with CFG distillation,\n",
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"# so it's not _actually_ doing CFG at inference time.\n",
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"# Also, if you are generating a dialog, you should have at least two voices in the list.\n",
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"# Also, if you are generating a dialog, you should have two voices in the list.\n",
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"condition_attributes = tts_model.make_condition_attributes(\n",
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" [voice_path], cfg_coef=2.0\n",
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")"
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@ -79,8 +79,6 @@
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"print(\"Generating audio...\")\n",
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"\n",
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"pcms = []\n",
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"\n",
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"@torch.no_grad()\n",
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"def _on_frame(frame):\n",
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" print(\"Step\", len(pcms), end=\"\\r\")\n",
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" if (frame != -1).all():\n",
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